Estimating the elasticity of substitution when compiling the CES cost of living index on scanner data

Abstract

Scanner data are electronic transaction data that specify turnover and the number of items sold by barcodes, e.g., the Global Trade Article Number. These data are of particular value and interest to theorists and practitioners who wish to measure the Cost of Living Index or the Consumer Price Index, since their complete content makes it possible to compute any price index formula, including superlative indices or CES (Constant Elasticity Substitution) indices. Since the CES index requires the estimation of the elasticity of substitution, this paper focuses on verifying various methods of estimating this parameter based on scanner data. The paper considers both algebraic methods and methods based on the panel regression approach. The main achievement of the paper is the separation of the main factors that affect the estimated value of the elasticity of substitution, i.e., the type of data filter used and the level of data aggregation. The paper also verifies how the elasticity of substitution estimates affect the differences between the values of the CES indices based on these estimates.